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Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Iris Recognition is a challenging problem. Numerous research contributions are available in literature related to iris recognition and feature extraction but the current trend of wavelet and multiwavelet for iris image feature extraction are given special attention in this book. This book covers the development of an iris recognition system to verify the uniqueness of human iris and find its performance as a biometric. An effort has been made to address the real time challenges faced at the time of iris image segmentation and normalization. From the normalized block, feature are extracted using wavelet and multiwavelet. Feature level fusion technique has been also employed to find the best technique for feature extraction and to get most compact features.…

Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Khobragade KavitaDr. Kavita Khobragade, working as Associate Professor in Computer Science Department, Fergusson College (Autonomous), Pune, (MS), India from last 21 years and completed her Ph.D. from Dr. Babasaheb Ambedkar Marathwa.…

Kartoniert / Broschiert. Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Mane ArjunDr. Arjun Vithalrao Mane completed PhD in Computer Science from Dr. Babasaheb Ambedkar Marathwada University, Aurangabad. Currently working as an Assistant Professor in the Institute of Forensic Science, Nagpur (MS-India). .…

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Taschenbuch. Condizione: Neu. Generative Adversarial Networks for Remote Sensing | Amol Dattatraya Vibhute (u. a.) | Taschenbuch | Englisch | 2025 | IGI Global | EAN 9798369369012 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand. …

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Generative adversarial networks (GANs) are transforming the way complex remote sensing data is analyzed, offering innovative solutions for geospatial applications. Traditional methods often struggle to process high-dimensional remotely sensed datasets, leading to limitations in decision-making and predictive accuracy. By leveraging GANs, researchers can enhance feature extraction, object detection, and time-series analysis, enabling more precise environmental monitoring, urban planning, and agricultural assessments. This technological advancement not only improves real-time geospatial analysis but also opens new avenues for interdisciplinary collaboration, ethical considerations, and security challenges in AI-driven remote sensing. As GANs continue to evolve, their application in remote sensing holds the potential to drive sustainability and more informed global decision-making. Generative Adversarial Networks for Remote Sensing emphasizes the foundations of recent trends in GANs and remote sensing applications. It provides insights into the fundamentals of generative adversarial networks, historical advancements, novel GAN architectures and challenges in analyzing remote sensing data using GANs. Covering topics such as change detection, resource management, and feature engineering, this book is an excellent resource for geographers, geospatial data analysts, engineers, professionals, researchers, scholars, academicians, and more.…

Buch. Condizione: Neu. Generative Adversarial Networks for Remote Sensing | Amol Dattatraya Vibhute (u. a.) | Buch | Englisch | 2025 | IGI Global | EAN 9798369369005 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.…

Buch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Generative adversarial networks (GANs) are transforming the way complex remote sensing data is analyzed, offering innovative solutions for geospatial applications. Traditional methods often struggle to process high-dimensional remotely sensed datasets, leading to limitations in decision-making and predictive accuracy. By leveraging GANs, researchers can enhance feature extraction, object detection, and time-series analysis, enabling more precise environmental monitoring, urban planning, and agricultural assessments. This technological advancement not only improves real-time geospatial analysis but also opens new avenues for interdisciplinary collaboration, ethical considerations, and security challenges in AI-driven remote sensing. As GANs continue to evolve, their application in remote sensing holds the potential to drive sustainability and more informed global decision-making. Generative Adversarial Networks for Remote Sensing emphasizes the foundations of recent trends in GANs and remote sensing applications. It provides insights into the fundamentals of generative adversarial networks, historical advancements, novel GAN architectures and challenges in analyzing remote sensing data using GANs. Covering topics such as change detection, resource management, and feature engineering, this book is an excellent resource for geographers, geospatial data analysts, engineers, professionals, researchers, scholars, academicians, and more.…